The aim of this paper is to identify Nano-particles that have been used in diagnosis and treatment of leishmaniasis in Iraq. All experiments conducted in this field were based on the following nanoparticles: gold nanoparticles, silver nanoparticles, zinc nanoparticles, and sodium chloride nanoparticles. Most of these experiments were reviewed in terms of differences in the concentrations of nanoparticles and the method that was used in the experiments whether it was in vivo or in vitro. These particles used in most experiments succeeded in inhibiting the growth of Leishmania parasites.

Recent population studies have shown that placenta accreta spectrum (PAS) disorders remain undiagnosed before delivery in half to two-thirds of cases. In a series from specialist diagnostic units in the USA, around one-third of cases of PAS disorders were not diagnosed during pregnancy. Maternal

The ceiling of the midbrain has a couple of optic lobes which are prominent and used as an optic center that reflex what it receives from eye retina fibers. The histology of optic tectum has been studied in Iraqi fish Barbus luteus (Heckel) . It was found that the number of optic tectum were six main strata organized from the outside to the inside as follows : the stratum marginal (SM), the stratum opticum (SO), the stratum fibrosum et griseum superficialis (SFGS), the stratum griseum central (SGC), the stratum album central (SAC), the stratum periventricular (SPV), . the tow last strata consider deep layers on the optic tectum. It was noticed that the superficial strata was the first (SM), while the thickest strata was the four (SGC), whic

Shehadt 683 fish of different fish present in the tank Haditha Dam during the period of February 1993 and the end Maes 1994 to identify the nutritional content of the digestive tract or the stomach for these fish and their impact on the environment of the tank and found that Fish fine linen and Alhalg animal feeding predators feed on small fish, mainly the fish brown plantnutrition

The fish assemblage in the East Hammar marsh was studied during December 2009 to May 2010. The fish fauna of the marsh consisted of 17 native, 23 marine (49%) and seven alien species. The dominant species were Liza abu (14.6%), Carassius auratus (13.4%) and Thryssa mystax (11.2%). The resident species formed 44.7%, occasional species 36.1% and seasonal species 19.2% of the total number of fish species. Fish species diversity index ranged from 1.28 to 2.61, richness from 1.98 to 4.50 and evenness from 0.45 to 0.78. Salinity ranged from 1.45 to 7.74‰. The increase in the proportion of marine species (49%) in the fish assemblage due to marine waters progress from Arabian Gulf had an impact on the values of ecological indices and the

   In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the  traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings